The residential real estate industry in the US has $1.6T in annual sales and $60B in annual gross brokerage commissions. The residential real estate brokerage industry has traditionally been very labor intensive, and the industry relies heavily on individual real estate agents working as independent contractors to provide services and to manage business transactions. Although information technology has been utilized in the industry, there are still problems such as: (a) inefficient real estate search, (b) unintuitive user interface for real estate search, (c) scattered open house information, and (d) inefficient real estate evaluation. The problems are described below.
(a) Inefficient Real Estate Search
Typically, when searching for real estate properties (hereinafter properties) on the market, an agent or prospective buyer would access a Property Information Database (PID) or one or more other databases that store syndicated information from the PID. PID systems are individually owned by local Realtor associations, and they include some basic data for each listed property. When a real estate agent obtains an agreement to sell a property, the agent (called a listing agent) usually puts information about that property into a PID system immediately so that other agents can view that information through the Internet. The completeness and accuracy of the information about a property on the market depends on what data the listing agent inputs. Frequently, the information in the PID is not accurate, or some pertinent information is missing. The inconsistent availability of data presents a challenge for the real estate agent trying to serve prospective buyers, and for the prospective buyers themselves, because they cannot assess the suitability of an inadequately listed property very easily. The prospective buyers will then have to physically visit such properties to evaluate their suitability. This presents a cost and efficiency challenge for both the agents and the prospective buyers.
Further, the PID contains only data that are intrinsic to individual properties, such as address, size, structure, and price. However, there are other extrinsic factors that a prospective buyer needs to or would like to consider when making a buying decision such as, for example and without limitation, surrounding amenities and facilities. FIGS. 12A-D illustrate differences between a conventional search result and a preferred search result. For an illustrative example, FIG. 12 shows houses such as houses 1202, 1204, 1206, 1208, 1212, 1214, and possibly other houses (represented by dotted lines) that meet a prospective buyer's search criteria of intrinsic data. As an example and as illustrated in FIG. 12B, a conventional search result will list all the above houses and many others as long as their data meet the prospective buyer's search criteria. Such a conventional search may list a large number of houses such that the prospective buyer is required to unnecessarily spend much time in skimming through listed data and is prevented from efficient and effective assessment of the houses. The conventional search result may further rank the houses according to their locations, or their distances to office 1232 (or a specified address) and list house 1202 the first, house 1204 the second, and so forth, without considering extrinsic factors.
(b) Unintuitive User Interface for Real Estate Search
In searching for properties, typical computer software programs and Internet websites allow users to enter search criteria by selecting given attributes or typing a keyword or a phrase in a text box.
FIG. 13A illustrates selections of attributes. As shown in FIG. 13A, a user may select the given attributes using a number of methods such as selecting a city from drop-down box 1302, checking boxes such as box 1304 for multiple choices such as property types, clicking on radio buttons such as radio button 1306 for alternative selections such as numbers of bedrooms and bathrooms, entering numbers in text boxes such as text box 1308 for entering data such as price limits, etc. However, these methods require the user to unnecessarily and discretely go through many menus of options and attributes to enter their selection criteria. Such structured search options limit the user's thinking and do not provide an intuitive way for the user to think about the kind of real estate properties that the user himself/herself is really looking for.
FIG. 13B illustrates a text box, in which the user may type a keyword such as “post office” as a criterion for searching for a house for which the data in PID contain the keyword (or “post office” in this example). However, a search based on a single criterion may list an unnecessarily large number of real estate properties that meet the criterion and make it difficult for the user to efficiently and effectively find desirable properties. The user may also be allowed to type a logical combination using one or more logic operators such as “AND” and “OR” to provide multiple search criteria. Nevertheless, the logic operators are not intuitive to many users who do not have relevant training.
Again, the typical computer software programs and Internet websites provide searches only in PIDs, which do not include extrinsic factors that are also important for the user's buying decision.
(c) Scattered Open House Information
Open houses, commonly hosted during Sundays or Saturday afternoons, are times when properties on the market are open to the public for viewing. Prospective buyers, sellers, neighbors, or agents view the properties at these open houses. There exists a problem in communicating to the public when and which properties are holding open houses during a particular weekend.
There are several ways that sellers currently give notice of their open houses. A seller or agent can advertise in local or regional newspapers, put the information on the local PID board, put the information directly into the marketing comments in the PID that can be viewed by the public or by the agents, place broker advertisements that include property information as well as open house information, or disperse specific printed or online materials that individual real estate agents put together. Sometimes, open house information is not publicly available, and is thus only obtainable by calling the listing agent. Given scattered or even unavailable sources, end consumers, i.e. the prospective buyers, cannot easily access open house information. There currently exists no streamlined way for buyers to find a comprehensive list of the open houses for a particular Sunday, for example. A buyer would have to consult multiple sources to extract that information. Such a labor-intensive approach is neither efficient nor reliable.
Further, useful information generated during open house tours are not efficiently and sufficiently collected. A typical open house tour process that agents or prospective buyers follow includes reviewing currently available listings of open houses, selecting suitable properties for viewing, locating these properties on maps, getting driving directions for the tour, physically visiting these properties, viewing the various neighborhoods surrounding these properties, recording personal impressions and other information about properties either mentally or on paper or other electronic means, and finally identifying particular homes in which the buyers maybe interested. Often when the buyers view the properties on open house tours on their own, the agents working with them do not get the information on how and why the buyers like or dislike about these properties. That information could be very important for the agents in the future to help identify the properties that may be appropriate for their clients, but existing practices do not allow agents to exploit such information.
(d) Inefficient Real Estate Evaluation
There can be hundreds of residential properties that become available on the market in a week in a particular city. Prospective buyers and real estate agents typically have to evaluate these homes to see if they are suitable candidates for purchase, and also to figure out whether these properties are of good values. This task of evaluating whether a specific property is of good value involves very complicated and time-consuming task of comparing this property against personal preferences, previously sold homes and their prices, currently available homes and their offered prices, housing and other financial trends, etc. This task currently is handled manually by the particular prospective buyers or real estate agents, and to do this accurately, one needs to process a lot of data. This manual processing of data can become a prohibitively time-consuming task if one chooses to consider a large number of properties.
One of the most important criteria for prospective buyers in selecting properties is whether the property is attractively priced. To figure out whether a property is attractively or cheaply priced, the buyer needs to seek professional help from appraisers and real estate agents. The process is very time consuming and expensive, and therefore most often buyers cannot easily screen for well-priced properties. When a large number of properties are on the market, the buyer may therefore miss out on good deals, because he cannot readily and cost-effectively identify the for-sale properties that offer the most value.
In light of the above, there is a need in the art for one or more methods or apparatuses that solve one or more above-identified problems. In light of the above, there is a need in the art for one or more methods or apparatuses that solve one or more above-identified problems pertaining to unintuitive user interface for real estate search.